SoroushVahidi/scidocs huggingface dataset:
CREDAL: Towards Locating a Memory Corruption Vulnerability with Your Core Dump
(2016)

After a program has crashed and terminated abnormally, it typically leaves behind a snapshot of its crashing state in the form of a core dump. While a core dump carries a large amount of information, which has long been used for software debugging, it barely serves as informative debugging aids in locating software faults, particularly memory corruption vulnerabilities. A memory corruption vulnerability is a special type of software faults that an attacker can exploit to manipulate the content at a certain memory. As such, a core dump may contain a certain amount of corrupted data, which increases the difficulty in identifying useful debugging information (e.g. , a crash point and stack traces). Without a proper mechanism to deal with this problem, a core dump can be practically useless for software failure diagnosis. In this work, we develop CREDAL, an automatic tool that employs the source code of a crashing program to enhance core dump analysis and turns a core dump to an informative aid in tracking down memory corruption vulnerabilities. Specifically, CREDAL systematically analyzes a core dump potentially corrupted and identifies the crash point and stack frames. For a core dump carrying corrupted data, it goes beyond the crash point and stack trace. In particular, CREDAL further pinpoints the variables holding corrupted data using the source code of the crashing program along with the stack frames. To assist software developers (or security analysts) in tracking down a memory corruption vulnerability, CREDAL also performs analysis and highlights the code fragments corresponding to data corruption.
 To demonstrate the utility of CREDAL, we use it to analyze 80 crashes corresponding to 73 memory corruption vulnerabilities archived in Offensive Security Exploit Database. We show that, CREDAL can accurately pinpoint the crash point and (fully or partially) restore a stack trace even though a crashing program stack carries corrupted data. In addition, we demonstrate CREDAL can potentially reduce the manual effort of finding the code fragment that is likely to contain memory corruption vulnerabilities.
Multiple PRP injections are more effective than single injections and hyaluronic acid in knees with early osteoarthritis: a randomized, double-blind, placebo-controlled trial
(2015)

To compare the effectiveness of intraarticular (IA) multiple and single platelet-rich plasma (PRP) injections as well as hyaluronic acid (HA) injections in different stages of osteoarthritis (OA) of the knee. A total of 162 patients with different stages of knee OA were randomly divided into four groups receiving 3 IA doses of PRP, one dose of PRP, one dose of HA or a saline injection (control). Then, each group was subdivided into two groups: early OA (Kellgren–Lawrence grade 0 with cartilage degeneration or grade I–III) and advanced OA (Kellgren–Lawrence grade IV). The patients were evaluated before the injection and at the 6-month follow-ups using the EuroQol visual analogue scale (EQ-VAS) and International Knee Documentation Committee (IKDC) subjective scores. Adverse events and patient satisfaction were recorded. There was a statistically significant improvement in the IKDC and EQ-VAS scores in all the treatment groups compared with the control group. The knee scores of patients treated with three PRP injections were significantly better than those patients of the other groups. There was no significant difference in the scores of patients injected with one dose of PRP or HA. In the early OA subgroups, significantly better clinical results were achieved in the patients treated with three PRP injections, but there was no significant difference in the clinical results of patients with advanced OA among the treatment groups. The clinical results of this study suggest IA PRP and HA treatment for all stages of knee OA. For patients with early OA, multiple (3) PRP injections are useful in achieving better clinical results. For patients with advanced OA, multiple injections do not significantly improve the results of patients in any group. I.
OpenFst: A General and Efficient Weighted Finite-State Transducer Library
(2007)

We describe OpenFst, an open-source library for weighted finite-state transducers (WFSTs). OpenFst consists of a C++ template library with efficient WFST representations and over twenty-five operations for constructing, combining, optimizing, and searching them. At the shell-command level, there are corresponding transducer file representations and programs that operate on them. OpenFst is designed to be both very efficient in time and space and to scale to very large problems. This library has key applications speech, image, and natural language processing, pattern and string matching, and machine learning. We give an overview of the library, examples of its use, details of its design that allow customizing the labels, states, and weights and the lazy evaluation of many of its operations. Further information and a download of the OpenFst library can be obtained from http://www.openfst.org.
Dynamical Approximation by Hierarchical Tucker and Tensor-Train Tensors
(2013)

We extend results on the dynamical low-rank approximation for the treatment of time-dependent matrices and tensors (Koch and Lubich; see [SIAM J. Matrix Anal. Appl., 29 (2007), pp. 434–454], [SIAM J. Matrix Anal. Appl., 31 (2010), pp. 2360–2375]) to the recently proposed hierarchical Tucker (HT) tensor format (Hackbusch and Kühn; see [J. Fourier Anal. Appl., 15 (2009), pp. 706–722]) and the tensor train (TT) format (Oseledets; see [SIAM J. Sci. Comput., 33 (2011), pp. 2295–2317]), which are closely related to tensor decomposition methods used in quantum physics and chemistry. In this dynamical approximation approach, the time derivative of the tensor to be approximated is projected onto the time-dependent tangent space of the approximation manifold along the solution trajectory. This approach can be used to approximate the solutions to tensor differential equations in the HT or TT format and to compute updates in optimization algorithms within these reduced tensor formats. By deriving and analyzing the tangent space projector for the manifold of HT/TT tensors of fixed rank, we obtain curvature estimates, which allow us to obtain quasi-best approximation properties for the dynamical approximation, showing that the prospects and limitations of the ansatz are similar to those of the dynamical low rank approximation for matrices. Our results are exemplified by numerical experiments.
Statistics and Social Network of YouTube Videos
(2008)

YouTube has become the most successful Internet website providing a new generation of short video sharing service since its establishment in early 2005. YouTube has a great impact on Internet traffic nowadays, yet itself is suffering from a severe problem of scalability. Therefore, understanding the characteristics of YouTube and similar sites is essential to network traffic engineering and to their sustainable development. To this end, we have crawled the YouTube site for four months, collecting more than 3 million YouTube videos' data. In this paper, we present a systematic and in-depth measurement study on the statistics of YouTube videos. We have found that YouTube videos have noticeably different statistics compared to traditional streaming videos, ranging from length and access pattern, to their growth trend and active life span. We investigate the social networking in YouTube videos, as this is a key driving force toward its success. In particular, we find that the links to related videos generated by uploaders' choices have clear small-world characteristics. This indicates that the videos have strong correlations with each other, and creates opportunities for developing novel techniques to enhance the service quality.
No-reference image and video quality assessment: a classification and review of recent approaches
(2014)

The field of perceptual quality assessment has gone through a wide range of developments and it is still growing. In particular, the area of no-reference (NR) image and video quality assessment has progressed rapidly during the last decade. In this article, we present a classification and review of latest published research work in the area of NR image and video quality assessment. The NR methods of visual quality assessment considered for review are structured into categories and subcategories based on the types of methodologies used for the underlying processing employed for quality estimation. Overall, the classification has been done into three categories, namely, pixel-based methods, bitstream-based methods, and hybrid methods of the aforementioned two categories. We believe that the review presented in this article will be helpful for practitioners as well as for researchers to keep abreast of the recent developments in the area of NR image and video quality assessment. This article can be used for various purposes such as gaining a structured overview of the field and to carry out performance comparisons for the state-of-the-art
Improving Machine Learning Approaches to Coreference Resolution
(2002)

Wepresentanounphrasecoreferencesystem that extends the work of Soon et al. (2001) and, to our knowledge, producesthebestresultsto dateontheMUC6 andMUC-7 coreferenceresolutiondata sets— F-measuresof 70.4 and63.4, respecti vely. Improvementsarisefrom two sources: extra-linguistic changesto the learningframework anda large-scaleexpansionof thefeaturesetto includemore sophisticatedlinguisticknowledge.
Genital trauma and vaginal bleeding: is it a lapse of time issue? A case report of a prepubertal girl and review of the literature
(2016)

Child victims of sexual abuse may present with physical findings whose interpretation requires the most exhaustive evaluation and an accurate collection of a detailed history. Genital bleeding is usually considered as an acute sign, related to a trauma that occurred shortly before its appearance. We report a case of a 34-month-old child who was referred to the emergency room with a significant vaginal hemorrhage, originating from a wide laceration of the posterior fourchette, and a negative history for accidental trauma. The characteristics of the lesion, compared to the temporal evolution of the healing process, and the witnesses’ depositions led us to assume that the time elapsed between the abusive event and the physical examination was longer in respect to what had appeared at the first sight. The judicial reconstruction of the events confirmed our assumption, allowing the charge of the right abuse perpetrator. As the literature regarding this eventuality is very poor, we report this case to stress the importance for physicians to consider that an active bleeding may be the manifestation of a trauma that occurred very long before.
Novel Compact Tri-Band Bandpass Filter With Controllable Bandwidths
(2011)

Novel compact tri-band bandpass filter (BPF) with controllable bandwidths is presented in this letter. The tri-band performance is realized by using three sets of resonators, i.e., two sets of short-stub loaded dual-mode resonators, which are designed for the first and second passband, respectively, and half-wavelength resonators for the third passband. The three passband frequencies and bandwidths could be independently tuned and designed. The half-wavelength resonators are embedded between the two dual-mode resonators and serve as part of feed lines for the first and second passband, thus compact size is realized. The newly designed tri-band BPF is verified by circuit implementation and good agreement between the simulated and measured results can be observed.
Snap, Eat, RepEat: A Food Recognition Engine for Dietary Logging
(2016)

We present a system to assist users in dietary logging habits, which performs food recognition from pictures snapped on their phone in two different scenarios. In the first scenario, called "Food in context", we exploit the GPS information of a user to determine which restaurant they are having a meal at, therefore restricting the categories to recognize to the set of items in the menu. Such context allows us to also report precise calories information to the user about their meal, since restaurant chains tend to standardize portions and provide the dietary information of each meal. In the second scenario, called "Foods in the wild" we try to recognize a cooked meal from a picture which could be snapped anywhere. We perform extensive experiments on food recognition on both scenarios, demonstrating the feasibility of our approach at scale, on a newly introduced dataset with 105K images for 500 food categories.
A Tandem Algorithm for Singing Pitch Extraction and Voice Separation From Music Accompaniment
(2012)

Singing pitch estimation and singing voice separation are challenging due to the presence of music accompaniments that are often nonstationary and harmonic. Inspired by computational auditory scene analysis (CASA), this paper investigates a tandem algorithm that estimates the singing pitch and separates the singing voice jointly and iteratively. Rough pitches are first estimated and then used to separate the target singer by considering harmonicity and temporal continuity. The separated singing voice and estimated pitches are used to improve each other iteratively. To enhance the performance of the tandem algorithm for dealing with musical recordings, we propose a trend estimation algorithm to detect the pitch ranges of a singing voice in each time frame. The detected trend substantially reduces the difficulty of singing pitch detection by removing a large number of wrong pitch candidates either produced by musical instruments or the overtones of the singing voice. Systematic evaluation shows that the tandem algorithm outperforms previous systems for pitch extraction and singing voice separation.
A spaceborne telemetry loaded bifilar helical antenna for LEO satellites
(2009)

In this paper we describe the design, manufacturing and measurement of an antenna with an isoflux type radiation pattern used in the space segment TT&C subsystem. In particular, the antenna corresponds to the flight model of mission SAC-D/AQUARIUS, which is a LEO earth observation satellite. The chosen solution is a loaded bifilar helical antenna, which presents a higher gain than a typical hemispherical antenna but which doesn't require the use of a beam forming network like the classical quadrifilar Kilgus type antenna. This reduces the number of required parts, and due to its loading, smaller dimension and higher structural stiffness are achieved.
Sampling Large Databases for Association Rules
(1996)

Discovery of association rules is an important database mining problem. Current algorithms for nding association rules require several passes over the analyzed database, and obviously the role of I/O overhead is very signi cant for very large databases. We present new algorithms that reduce the database activity considerably. The idea is to pick a random sample, to nd using this sample all association rules that probably hold in the whole database, and then to verify the results with the rest of the database. The algorithms thus produce exact association rules, not approximations based on a sample. The approach is, however, probabilistic, and in those rare cases where our sampling method does not produce all association rules, the missing rules can be found in a second pass. Our experiments show that the proposed algorithms can nd association rules very e ciently in only one database pass.
Mining Quantitative Association Rules in Large Relational Tables
(1996)

We introduce the problem of mining association rules in large relational tables containing both quantitative and categorical attributes. An example of such an association might be "10% of married people between age 50 and 60 have at least 2 cars". We deal with quantitative attributes by fine-partitioning the values of the attribute and then combining adjacent partitions as necessary. We introduce measures of partial completeness which quantify the information lost due to partitioning. A direct application of this technique can generate too many similar rules. We tackle this problem by using a "greater-than-expected-value" interest measure to identify the interesting rules in the output. We give an algorithm for mining such quantitative association rules. Finally, we describe the results of using this approach on a real-life dataset.
Rethinking Education in the Age of Technology
(2008)

By reading, you can know the knowledge and things more, not only about what you get from people to people. Book will be more trusted. As this rethinking education in the age of technology review, it will really give you the good idea to be successful. It is not only for you to be success in certain life you can be successful in everything. The success can be started by knowing the basic knowledge and do actions.
Pathophysiological distortions in time perception and timed performance.
(2012)

Distortions in time perception and timed performance are presented by a number of different neurological and psychiatric conditions (e.g. Parkinson's disease, schizophrenia, attention deficit hyperactivity disorder and autism). As a consequence, the primary focus of this review is on factors that define or produce systematic changes in the attention, clock, memory and decision stages of temporal processing as originally defined by Scalar Expectancy Theory. These findings are used to evaluate the Striatal Beat Frequency Theory, which is a neurobiological model of interval timing based upon the coincidence detection of oscillatory processes in corticostriatal circuits that can be mapped onto the stages of information processing proposed by Scalar Timing Theory.
User Traffic Profile for Traffic Reduction and Effective Bot C&C Detection
(2014)

Bots are malicious software components used for generating spams, launching denial of service attacks, phishing, identity theft and information exfiltration and such other illegal activities. Bot detection is an area of active research in recent times. Here we propose a bot detection mechanism for a single host. A user traffic profile is used to filter out normal traffic generated by the host. The remaining suspicious traffic is subject to detailed analysis. The nature of detailed analysis is derived from a characterization of bot traffic. The detection system is tested using two real world bots. Performance evaluation results show that the proposed system achieves a high detection rate (100%) and a low false positive rate (0–8%). The traffic filtering yielded an average reduction in traffic by 70%.
PreCog: Improving Crowdsourced Data Quality Before Acquisition
(2017)

Quality control in crowdsourcing systems is crucial. It is typically done after data collection, often using additional crowdsourced tasks to assess and improve the quality. These post-hoc methods can easily add cost and latency to the acquisition process—particularly if collecting high-quality data is important. In this paper, we argue for pre-hoc interface optimizations based on feedback that helps workers improve data quality before it is submitted and is well suited to complement post-hoc techniques. We propose the Precog system that explicitly supports such interface optimizations for common integrity constraints as well as more ambiguous text acquisition tasks where quality is ill-defined. We then develop the Segment-Predict-Explain pattern for detecting low-quality text segments and generating prescriptive explanations to help the worker improve their text input. Our unique combination of segmentation and prescriptive explanation are necessary for Precog to collect 2× more high-quality text data than non-Precog approaches on two real domains.
ZenCrowd: leveraging probabilistic reasoning and crowdsourcing techniques for large-scale entity linking
(2012)

We tackle the problem of entity linking for large collections of online pages; Our system, ZenCrowd, identifies entities from natural language text using state of the art techniques and automatically connects them to the Linked Open Data cloud. We show how one can take advantage of human intelligence to improve the quality of the links by dynamically generating micro-tasks on an online crowdsourcing platform. We develop a probabilistic framework to make sensible decisions about candidate links and to identify unreliable human workers. We evaluate ZenCrowd in a real deployment and show how a combination of both probabilistic reasoning and crowdsourcing techniques can significantly improve the quality of the links, while limiting the amount of work performed by the crowd.
Nonspeech oral motor treatment issues related to children with developmental speech sound disorders.
(2008)

PURPOSE
This article examines nonspeech oral motor treatments (NSOMTs) in the population of clients with developmental speech sound disorders. NSOMTs are a collection of nonspeech methods and procedures that claim to influence tongue, lip, and jaw resting postures; increase strength; improve muscle tone; facilitate range of motion; and develop muscle control. In the case of developmental speech sound disorders, NSOMTs are employed before or simultaneous with actual speech production treatment.


METHOD
First, NSOMTs are defined for the reader, and there is a discussion of NSOMTs under the categories of active muscle exercise, passive muscle exercise, and sensory stimulation. Second, different theories underlying NSOMTs along with the implications of the theories are discussed. Finally, a review of pertinent investigations is presented.


RESULTS
The application of NSOMTs is questionable due to a number of reservations that include (a) the implied cause of developmental speech sound disorders, (b) neurophysiologic differences between the limbs and oral musculature, (c) the development of new theories of movement and movement control, and (d) the paucity of research literature concerning NSOMTs.


CLINICAL IMPLICATION
There is no substantive evidence to support NSOMTs as interventions for children with developmental speech sound disorders.
Precise Flow-Insensitive May-Alias Analysis is NP-Hard
(1997)

Determining aliases is one of the foundamental static analysis problems, in part because the precision with which this problem is solved can affect the precision of other analyses such as live variables, available expressions, and constant propagation. Previous work has investigated the complexity of flow-sensitive alias analysis. In this article we show that precise flow-insensitive may-alias analysis is NP-hard given arbitrary levels of pointers and arbitrary pointer dereferencing.